We present a procedure for the identiÿcation of clusters in multivariate data sets, based on the comparison between the k nearest neighbors graph, G k , and the minimal spanning tree, MST. Our key statistic is the random quantity k := the smallest k such that G k contains the MST. Under regularity a
Connectivity of the mutual k-nearest-neighbor graph in clustering and outlier detection
✍ Scribed by M.R. Brito; E.L. Chávez; A.J. Quiroz; J.E. Yukich
- Publisher
- Elsevier Science
- Year
- 1997
- Tongue
- English
- Weight
- 610 KB
- Volume
- 35
- Category
- Article
- ISSN
- 0167-7152
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✦ Synopsis
For multivariate data sets, we study the relationship between the connectivity of a mutual k-nearest-neighbor graph, and the presence of clustering structure and outliers in the data. A test for detection of clustering structure and outliers is proposed and its performance is evaluated in simulated data.
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